A quantitative structure-permeability relationship model for split-thickness skin absorption, reasoning for the choice of the database.

The skin is the largest organ in the human body, protecting the body from xenobiotic invasion (1). Local and systemic drugs may also be administered through the skin, therefore the need to measure the permeability of the skin to chemicals has long been apparent. The use of in vivo or in vitro techniques is time-consuming, since it is not only necessary to conduct a permeation study, but also to optimize experimental conditions and build analytical methods for each chemical. Moreover, it is not possible to assess the permeability of compounds not yet synthesised. An alternative option can be the development of Quantitative Structure-Permeability Relationships (QSPRs). These in silico models aim to form a relationship between the absorption of chemicals through the skin and their physico-chemical and/or structural properties (2). Knowing that permeability can be affected by different experimental conditions, the aim of this study is to build a QSPR based on uniform and consistent experimental conditions, but with a significant database size. Two different databases were compared: the first one was obtained only from Zhang et al (3), the second one was created from multiple literature sources, fulfilling the following conditions: - Data (log Kp values) were obtained by an in vitro diffusion system; - The membrane was human stratum corneum and viable epidermis; - The donor solvent was an aqueous solution; - No permeation enhancement technologies were used; - No association with other chemicals were considered. The geometrical structures of all chemicals were optimized with MM2 forcefield. Molecular descriptors and fingerprints were generated where possible. For each database, a wide range of Multi Linear Regression models were built using QSARins (4, 5) through a stepwise forward regression process. The models have been validated according to Golbraikh and Tropsha (6) criteria and the best ones have been selected according to the Multi-Criteria Decision Making (7). The model calculated from the data obtained from a single source shows better correlation, robustness, and predictivity, revealing a grade of uncertainty coming from an inter laboratory variability of the different sources used to build the database. REFERENCES 1. Baba H, Takahara J-i, Mamitsuka H. In Silico Predictions of Human Skin Permeability using Nonlinear Quantitative Structure–Property Relationship Models. Pharmaceutical Research. 2015;32(7):2360-71. 2. Moss GP, Cronin MTD. Quantitative structure–permeability relationships for percutaneous absorption: re-analysis of steroid data. International Journal of Pharmaceutics. 2002;238(1):105-9. 3. Zhang K, Chen M, Scriba GKE, Abraham MH, Fahr A, Liu X. Human Skin Permeation of Neutral Species and Ionic Species: Extended Linear Free Energy Relationship Analyses. Journal of Pharmaceutical Sciences. 2012;101(6):2034-44. 4. Gramatica P, Chirico N, Papa E, Cassani S, Kovarich S. QSARINS: A new software for the development, analysis, and validation of QSAR MLR models. Journal of Computational Chemistry. 2013;34(24):2121-32. 5. Gramatica P, Cassani S, Chirico N. QSARINS-chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS. Journal of Computational Chemistry. 2014;35(13):1036-44. 6. Golbraikh A, Tropsha A. Beware of q2! Journal of Molecular Graphics and Modelling. 2002;20(4):269-76. 7. Keller HR, Massart DL, Brans JP. Multicriteria decision making: A case study. Chemometrics and Intelligent Laboratory Systems. 1991;11(2):175-89.Peer reviewedFinal Published versio

Predicting Skin Permeability by means of Computational Approaches : Reliability and Caveats in Pharmaceutical Studies

© 2019 American Chemical Society.The skin is the main barrier between the internal body environment and the external one. The characteristics of this barrier and its properties are able to modify and affect drug delivery and chemical toxicity parameters. Therefore, it is not surprising that permeability of many different compounds has been measured through several in vitro and in vivo techniques. Moreover, many different in silico approaches have been used to identify the correlation between the structure of the permeants and their permeability, to reproduce the skin behavior, and to predict the ability of specific chemicals to permeate this barrier. A significant number of issues, like interlaboratory variability, experimental conditions, data set building rationales, and skin site of origin and hydration, still prevent us from obtaining a definitive predictive skin permeability model. This review wants to show the main advances and the principal approaches in computational methods used to predict this property, to enlighten the main issues that have arisen, and to address the challenges to develop in future research.Peer reviewedFinal Accepted Versio

Effect of ethnicity, gender and age on the amount and composition of residual skin surface components derived from sebum, sweat and epidermal lipids

Background/purpose: The superficial layer on the skin surface, known as the acid mantle, comprises a mixture of sebum, sweat, corneocyte debris and constituents of natural moisturizing factor. Thus, the phrase 'residual skin surface components' (RSSC) is an appropriate term for the mixture of substances recovered from the skin surface. There is no general agreement about the effects of ethnicity, gender and age on RSSC. The aim of this human volunteer study was to evaluate RSSC in relation to ethnicity, gender and age. A suitable acquisition medium for RSSC collection was identified and samples of RSSC were subsequently analysed using gas chromatography-mass spectrometry (GC-MS) and gravimetry. Methods: A total of 315 volunteers participated in the study from a range of self-declared ethnic backgrounds. Six acquisition media were compared to determine the most suitable media for RSSC collection. The effect of age, gender and ethnicity on RSSC collection was evaluated by gravimetric analysis while GC-MS was used to determine the composition of RSSC. Results: Of the six candidate materials assessed, cigarette paper provided the most practical and reproducible sample acquisition medium. There was no significant difference in the amount of RSSC collected when based on gender and ethnic

Sebomic identification of sex- and ethnicity-specific variations in residual skin surface components (RSSC) for bio-monitoring or forensic applications

Background: “Residual skin surface components” (RSSC) is the collective term used for the superficial layer of sebum, residue of sweat, small quantities of intercellular lipids and components of natural moisturising factor present on the skin surface. Potential applications of RSSC include use as a sampling matrix for identifying biomarkers of disease, environmental exposure monitoring, and forensics (retrospective identification of exposure to toxic chemicals). However, it is essential to first define the composition of “normal” RSSC. Therefore, the aim of the current study was to characterise RSSC to determine commonalities and differences in RSSC composition in relation to sex and ethnicity. Methods: Samples of RSSC were acquired from volunteers using a previously validated method and analysed by high-pressure liquid chromatography–atmospheric pressure chemical ionisation–mass spectrometry (HPLC-APCI-MS). The resulting data underwent sebomic analysis. Results: The composition and abundance of RSSC components varied according to sex and ethnicity. The normalised abundance of free fatty acids, wax esters, diglycerides and triglycerides was significantly higher in males than females. Ethnicity-specific differences were observed in free fatty acids and a diglyceride. Conclusions: The HPLC-APCI-MS method developed in this study was successfully used to analyse the normal composition of RSSC. Compositional differences in the RSSC can be attributed to sex and ethnicity and may reflect underlying factors such as diet, hormonal levels and enzyme expression.Peer reviewedFinal Published versio

The Incidence of Venous Thromboembolism in Children Following Colorectal Resection for Inflammatory Bowel Disease: A Multi-Center Study

Background/Purpose Children with inflammatory bowel disease (IBD) have increased risk for venous thromboembolism (VTE). We sought to determine incidence and risk factors for postoperative VTE in a multicenter cohort of pediatric patients undergoing colorectal resection for IBD. Methods Retrospective review of children ≤18 years who underwent colorectal resection for IBD from 2010 to 2016 was performed at four children's hospitals. Primary outcome was VTE that occurred between surgery and last follow-up. Factors associated with VTE were determined using univariable and multivariable analyses. Results Two hundred seventy-six patients were included with median age 15 years [13,17]. Forty-two children (15%) received perioperative VTE chemoprophylaxis, and 88 (32%) received mechanical prophylaxis. DVT occurred in 12 patients (4.3%) at a median of 14 days postoperatively [8,147]. Most were portomesenteric (n = 9, 75%) with the remaining catheter-associated DVTs in extremities (n = 3, 25%). There was no association with chemoprophylaxis (p > 0.99). On Cox regression, emergent procedure [HR 18.8, 95%CI: 3.18–111], perioperative plasma transfusion [HR 25.1, 95%CI: 2.4–259], and postoperative infectious complication [HR 10.5, 95%CI: 2.63–41.8] remained predictive of DVT. Conclusion Less than 5% of pediatric IBD patients developed postoperative VTE. Chemoprophylaxis was not protective but rarely used. Patients with risk factors identified in this study should be monitored or given prophylaxis for VTE

Roadmap for C9ORF72 in Frontotemporal Dementia and Amyotrophic Lateral Sclerosis: Report on the C9ORF72 FTD/ALS Summit

A summit held March 2023 in Scottsdale, Arizona (USA) focused on the intronic hexanucleotide expansion in the C9ORF72 gene and its relevance in frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS; C9ORF72-FTD/ALS). The goal of this summit was to connect basic scientists, clinical researchers, drug developers, and individuals affected by C9ORF72-FTD/ALS to evaluate how collaborative efforts across the FTD-ALS disease spectrum might break down existing disease silos. Presentations and discussions covered recent discoveries in C9ORF72-FTD/ALS disease mechanisms, availability of disease biomarkers and recent advances in therapeutic development, and clinical trial design for prevention and treatment for individuals affected by C9ORF72-FTD/ALS and asymptomatic pathological expansion carriers. The C9ORF72-associated hexanucleotide repeat expansion is an important locus for both ALS and FTD. C9ORF72-FTD/ALS may be characterized by loss of function of the C9ORF72 protein and toxic gain of functions caused by both dipeptide repeat (DPR) proteins and hexanucleotide repeat RNA. C9ORF72-FTD/ALS therapeutic strategies discussed at the summit included the use of antisense oligonucleotides, adeno-associated virus (AAV)-mediated gene silencing and gene delivery, and engineered small molecules targeting RNA structures associated with the C9ORF72 expansion. Neurofilament light chain, DPR proteins, and transactive response (TAR) DNA-binding protein 43 (TDP-43)-associated molecular changes were presented as biomarker candidates. Similarly, brain imaging modalities (i.e., magnetic resonance imaging [MRI] and positron emission tomography [PET]) measuring structural, functional, and metabolic changes were discussed as important tools to monitor individuals affected with C9ORF72-FTD/ALS, at both pre-symptomatic and symptomatic disease stages. Finally, summit attendees evaluated current clinical trial designs available for FTD or ALS patients and concluded that therapeutics relevant to FTD/ALS patients, such as those specifically targeting C9ORF72, may need to be tested with composite endpoints covering clinical symptoms of both FTD and ALS. The latter will require novel clinical trial designs to be inclusive of all patient subgroups spanning the FTD/ALS spectrum

Integration of GWAS SNPs and tissue specific expression profiling reveal discrete eQTLs for human traits in blood and brain

Our knowledge of the transcriptome has become much more complex since the days of the central dogma of molecular biology. We now know that splicing takes place to create potentially thousands of isoforms from a single gene, and we know that RNA does not always faithfully recapitulate DNA if RNA editing occurs. Collectively, these observations show that the transcriptome is amazingly rich with intricate regulatory mechanisms for overall gene expression, splicing, and RNA editing. Genetic variability can play a role in controlling gene expression, which can be identified by examining expression quantitative trait loci (eQTLs). eQTLs are genomic regions where genetic variants, including single nucleotide polymorphisms (SNPs) show a statistical association with expression of mRNA transcripts. In humans, many SNPs are also associated with disease, and have been identified using genome wide association studies (GWAS) but the biological effects of those SNPs are usually not known. If SNPs found in GWAS are also found in eQTLs, then one could hypothesize that expression levels may contribute to disease risk. Performing eQTL analysis with GWAS SNPs in both blood and brain, specifically the frontal cortex and the cerebellum, we found both shared and tissue unique eQTLS. The identification of tissue-unique eQTLs supports the argument that choice of tissue type is important in eQTL studies (Paper I). Aging is a complex process with the mechanisms underlying aging still being poorly defined. There is evidence that the transcriptome changes with age, and hence we used the brain dataset from our first paper as a discovery set, with an additional replication dataset, to investigate any aging-gene expression associations. We found evidence that many genes were associated with aging. We further found that there were more statically significant expression changes in the frontal cortex versus the cerebellum, indicating that brain regions may age at different rates. As the brain is a heterogeneous tissue including both neurons and non-neuronal cells, we used LCM to capture Purkinje cells as a representative neuronal type and repeated the age analysis. Looking at the discovery, replication and Purkinje cell datasets we found five genes with strong, replicated evidence of age-expression associations (Paper II). Being able to capture and quantify the depth of the transcriptome has been a lengthy process starting with methods that could only measure a single gene to genome-wide techniques such as microarray. A recently developed technology, RNA-Seq, shows promise in its ability to capture expression, splicing, and editing and with its broad dynamic range quantification is accurate and reliable. RNA-Seq is, however, data intensive and a great deal of computational expertise is required to fully utilize the strengths of this method. We aimed to create a small, well-controlled, experiment in order to test the performance of this relatively new technology in the brain. We chose embryonic versus adult cerebral cortex, as mice are genetically homogenous and there are many known differences in gene expression related to brain development that we could use as benchmarks for analysis testing. We found a large number of differences in total gene expression between embryonic and adult brain. Rigorous technical and biological validation illustrated the accuracy and dynamic range of RNA-Seq. We were also able to interrogate differences in exon usage in the same dataset. Finally we were able to identify and quantify both well-known and novel A-to-I edit sites. Overall this project helped us develop the tools needed to build usable pipelines for RNA-Seq data processing (Paper III). Our studies in the developing brain (Paper III) illustrated that RNA-Seq was a useful unbiased method for investigating RNA editing. To extend this further, we utilized a genetically modified mouse model to study the transcriptomic role of the RNA editing enzyme ADAR2. We found that ADAR2 was important for editing of the coding region of mRNA as a large proportion of RNA editing sites in coding regions had a statistically significant decrease in editing percentages in Adar2 -/-Gria2 R/R mice versus controls. However, despite indications in the literature that ADAR2 may also be involved in splicing and expression regulatory machinery we found no changes in gene expression or exon utilization in Adar2 -/-Gria2 R/R mice as compared to their littermate controls (Paper IV). In our final study, based on the methods developed in Papers III and IV, we revisited the idea of age related gene expression associations from Paper II. We used a subset of human frontal cortices for RNA sequencing. Interestingly we found more gene expression changes with aging compared to the previous data using microarrays in Paper II. When the significant gene lists were analysed for gene ontology enrichment, we found that there was a large number of downregulated genes involved in synaptic function while those that were upregulated had enrichment in immune function. This dataset illustrates that the aging brain may be predisposed to the processes found in neurodegenerative diseases (Paper V)

C9ORF72 hexanucleotide repeat exerts toxicity in a stable, inducible motor neuronal cell model, which is rescued by partial depletion of Pten.

Amyotrophic lateral sclerosis (ALS) is a devastating and incurable neurodegenerative disease, characterised by progressive failure of the neuromuscular system. A (G4C2)n repeat expansion in C9ORF72 is the most common genetic cause of ALS and frontotemporal dementia (FTD). To date, the balance of evidence indicates that the (G4C2)n repeat causes toxicity and neurodegeneration via a gain-of-toxic function mechanism; either through direct RNA toxicity or through the production of toxic aggregating dipeptide repeat proteins. Here, we have generated a stable and isogenic motor neuronal NSC34 cell model with inducible expression of a (G4C2)102 repeat, to investigate the gain-of-toxic function mechanisms. The expression of the (G4C2)102 repeat produces RNA foci and also undergoes RAN translation. In addition, the expression of the (G4C2)102 repeat shows cellular toxicity. Through comparison of transcriptomic data from the cellular model with laser-captured spinal motor neurons from C9ORF72-ALS cases, we also demonstrate that the PI3K/Akt cell survival signalling pathway is dysregulated in both systems. Furthermore, partial knockdown of Pten rescues the toxicity observed in the NSC34 (G4C2)102 cellular gain-of-toxic function model of C9ORF72-ALS. Our data indicate that PTEN may provide a potential therapeutic target to ameliorate toxic effects of the (G4C2)n repeat

Genetic epidemiology of motor neuron disease-associated variants in the Scottish population

Genetic understanding of motor neuron disease (MND) has evolved greatly in the past 10 years, including the recent identification of association between MND and variants in TBK1 and NEK1. Our aim was to determine the frequency of pathogenic variants in known MND genes and to assess whether variants in TBK1 and NEK1 contribute to the burden of MND in the Scottish population. SOD1, TARDBP, OPTN, TBK1, and NEK1 were sequenced in 441 cases and 400 controls. In addition to 44 cases known to carry a C9orf72 hexanucleotide repeat expansion, we identified 31 cases and 2 controls that carried a loss-of-function or pathogenic variant. Loss-of-function variants were found in TBK1 in 3 cases and no controls and, separately, in NEK1 in 3 cases and no controls. This study provides an accurate description of the genetic epidemiology of MND in Scotland and provides support for the contribution of both TBK1 and NEK1 to MND susceptibility in the Scottish population

Multicenter external validation of the liverpool uveal melanoma prognosticator online: An OOG collaborative study

Uveal melanoma (UM) is fatal in ~50% of patients as a result of disseminated disease. This study aims to externally validate the Liverpool Uveal Melanoma Prognosticator Online V3 (LUMPO3) to determine its reliability in predicting survival after treatment for choroidal melanoma when utilizing external data from other ocular oncology centers. Anonymized data of 1836 UM patients from seven international ocular oncology centers were analyzed with LUMPO3 to predict the 10-year survival for each patient in each external dataset. The analysts were masked to the patient outcomes. Model predictions were sent to an independent statistician to evaluate LUMPO3’s performance using discrimination and calibration methods. LUMPO3’s ability to discriminate between UM patients who died of metastatic UM and those who were still alive was fair-to-good, with C-statistics ranging from 0.64 to 0.85 at year 1. The pooled estimate for all external centers was 0.72 (95% confidence interval: 0.68 to 0.75). Agreement between observed and predicted survival probabilities was generally good given differences in case mix and survival rates between different centers. Despite the differences between the international cohorts of patients with primary UM, LUMPO3 is a valuable tool for predicting all-cause mortality in this disease when using data from external centers